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    Research of Methods of Collision Warning and Avoidance Assistant Decision Making for the Ship in Typical Inland TSS Waters

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 002::page 04024023-1
    Author:
    Jiahao Chen
    ,
    Liwen Huang
    ,
    Ke Zhang
    ,
    Guozhu Hao
    ,
    Xingya Zhao
    ,
    Yixiong He
    DOI: 10.1061/AJRUA6.RUENG-1160
    Publisher: ASCE
    Abstract: Inland ship collisions in traffic separation scheme (TSS) water usually cause serious consequences. Research on ship collision risk early warning and collision avoidance assistant decision making can reduce the possibility of collision accidents caused by humans and reduce collision accidents and provide a basis for ships’ autonomous collision avoidance decisions. A digital traffic environment model for the typical inland TSS waters is constructed as the basis of navigation warning and decision making. A collision risk warning framework, which takes the intention of collision avoidance for the target ship into account, is established based on the dead reckoning and domain of the ship under TSS waterway constraints. In addition, a ship nonlinear maneuvering process deduction-based dynamic adaptive collision avoidance decision method is proposed under the premise of satisfying the Regulation of the People’s Republic of China on Inland River Collision Avoidance and good seamanship. The simulation experiments proved that the research could realize dynamic collision risk warnings under different encounter situations and provide effective assistant collision avoidance decisions in typical inland TSS waters.
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      Research of Methods of Collision Warning and Avoidance Assistant Decision Making for the Ship in Typical Inland TSS Waters

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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

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    contributor authorJiahao Chen
    contributor authorLiwen Huang
    contributor authorKe Zhang
    contributor authorGuozhu Hao
    contributor authorXingya Zhao
    contributor authorYixiong He
    date accessioned2024-04-27T22:39:20Z
    date available2024-04-27T22:39:20Z
    date issued2024/06/01
    identifier other10.1061-AJRUA6.RUENG-1160.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4297178
    description abstractInland ship collisions in traffic separation scheme (TSS) water usually cause serious consequences. Research on ship collision risk early warning and collision avoidance assistant decision making can reduce the possibility of collision accidents caused by humans and reduce collision accidents and provide a basis for ships’ autonomous collision avoidance decisions. A digital traffic environment model for the typical inland TSS waters is constructed as the basis of navigation warning and decision making. A collision risk warning framework, which takes the intention of collision avoidance for the target ship into account, is established based on the dead reckoning and domain of the ship under TSS waterway constraints. In addition, a ship nonlinear maneuvering process deduction-based dynamic adaptive collision avoidance decision method is proposed under the premise of satisfying the Regulation of the People’s Republic of China on Inland River Collision Avoidance and good seamanship. The simulation experiments proved that the research could realize dynamic collision risk warnings under different encounter situations and provide effective assistant collision avoidance decisions in typical inland TSS waters.
    publisherASCE
    titleResearch of Methods of Collision Warning and Avoidance Assistant Decision Making for the Ship in Typical Inland TSS Waters
    typeJournal Article
    journal volume10
    journal issue2
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.RUENG-1160
    journal fristpage04024023-1
    journal lastpage04024023-15
    page15
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 002
    contenttypeFulltext
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